Statistical Inference Based on the likelihood
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Adelchi Azzalini
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Density Function
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Equivalent Likelihoods
Exact MLE
exam
exponential
Exponential Families
family
Frequency Table
function
GLM Class
Likelihood Function
Likelihood Principle
Linear Independence
Linear Predictor
Log Linear Models
LRT
LRT Statistic
minimal
Minimal Sufficient Statistic
Newton Raphson Algorithm
Parametric Class
ple
Poisson Regression Model
random
Random Variable
Regular Exponential Families
Relative Likelihood
Sample Space
Saturated Model
Statistical Inference
sufficient
variable
Product details
- ISBN 9781032478012
- Weight: 880g
- Dimensions: 138 x 216mm
- Publication Date: 21 Jan 2023
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Paperback
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The Likelihood plays a key role in both introducing general notions of statistical theory, and in developing specific methods. This book introduces likelihood-based statistical theory and related methods from a classical viewpoint, and demonstrates how the main body of currently used statistical techniques can be generated from a few key concepts, in particular the likelihood.
Focusing on those methods, which have both a solid theoretical background and practical relevance, the author gives formal justification of the methods used and provides numerical examples with real data.
